Ensemble Model-based Clinical Decision Support System for Inherited Retinal Diseases in Pediatric Age

Abstract

In recent years, advancements in healthcare technology have paved the way for innovative approaches to clinical decision support systems (CDSS), especially in the context of inherited retinal diseases (IRD) affecting the pediatric population. IRD represent a group of genetically transmitted conditions that affect the structure and function of the retina, leading to visual impairment or blindness. The pediatric age group is particularly vulnerable to these diseases, necessitating early and accurate diagnosis for effective intervention and management. Traditional diagnostic systems for IRD often rely on a single approach, such as genetic testing, clinical examinations, or imaging techniques. While these methods have contributed significantly to our understanding of these diseases, their limitations in handling the complexity of genetic variations and the heterogeneity of disease manifestations underscore the need for a more sophisticated and integrated approach. Ensemble models offer a departure from the limitations of traditional systems by combining the strengths of various models, thereby improving diagnostic accuracy and reliability. Therefore, this research proposes an ensemble model based CDSS for inherited retinal diseases in the pediatric age group. By harnessing the power of diverse models, this approach can provide clinicians with a more comprehensive and accurate assessment of the underlying genetic factors and disease progression. Additionally, the proposed ensemble model based CDSS integrates diverse predictive models to enhance diagnostic accuracy and aid in the management of IRD in pediatric patients. Ultimately, the significance extends to improving patient outcomes, enabling earlier interventions, and contributing to the development of targeted therapies for IRD in the pediatric population.